@inbook{7161d1b1cb95483880726f548a605b5f,
title = "Statistical Characterization of the Optimal Detector for a Signal with Time-Varying Phase Based on the Edgeworth Series",
abstract = "This paper focuses on approximating the false alarm and detection probabilities of the optimal non-coherent detector for a signal, which contains a constant amplitude and unknown phase, corrupted by Gaussian noise. Several closed-form approximations of these probabilities are obtained using different truncations of the Edgeworth series and the Central Limit Theorem (CLT). The accuracy of the different approximations is contrasted to the performance of the optimal non-coherent detector revealing that the best approximation corresponds to the Edgeworth expansion using the longest series, which offers a great precision. The CLT approximation is not accurate enough to predict the performance of the optimal detector. The closed-form expression based on the Edgeworth series allows us to set a detection threshold for a false alarm probability value and obtain the detection probability of the detector with extreme accuracy.",
keywords = "CLT, detection threshold, Edgeworth series, post-detection integration techniques, ROC curves",
author = "David Gomez-Casco and Lopez-Salcedo, {Jose A.} and Gonzalo Seco-Granados",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",
year = "2018",
month = aug,
day = "29",
doi = "10.1109/SSP.2018.8450789",
language = "English",
isbn = "9781538615706",
series = "2018 IEEE Statistical Signal Processing Workshop, SSP 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "203--207",
booktitle = "2018 IEEE Statistical Signal Processing Workshop, SSP 2018",
address = "United States",
}